Data Analytics: Qualitative And Predictive Analyzed Computer Systems

Data analytics is the pursuit of extracting meaning from raw data using specialized computer systems. These systems transform, organize, and model the data to draw conclusions and identify patterns. Data Analytics is a method of collecting both qualitative and quantitative information about and therefore allowing managers to make informed decisions about their business processes.

Lawrence (2012) reported the biggest driver of development in the Human Resources area to be Predictive Analytics. He states that in previous years most people have made the mistake of talking about predictive analytics when they actually meant descriptive analytics i.e. reporting based on summary of historical events. Thus it makes sense to spend a few moments with the definitions of analysis, analytics and predictive analytics. As said, some believe that a single report on historical events equals an analysis or analytics. A report shows only one dimension of the topic under examination. Regardless how many reports you have in the past, you need to be able to interpret them and draw some conclusions, connections and insights between events and effects before you should state that the action taken has been “an analysis”. Thus an analysis can be defined as the interpretation of provided information

As an example of the most used implementation area in HR analytics would be predicting employee turnover or attrition. In the above mentioned framework, one would most likely first have just data stored in one or more databases on employees = step “Organize”. Then one would start to “Display” the data based on past events, for example in simple dashboards. After that phase one could “Relate” and benchmark the current data against other result in the industry, start “Modelling” to be able to predict the changes and finally take “Prescriptive” actions to manage the